• Title/Summary/Keyword: Similar information retrieval

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Application of Genetic and Local Optimization Algorithms for Object Clustering Problem with Similarity Coefficients (유사성 계수를 이용한 군집화 문제에서 유전자와 국부 최적화 알고리듬의 적용)

  • Yim, Dong-Soon;Oh, Hyun-Seung
    • Journal of Korean Institute of Industrial Engineers
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    • v.29 no.1
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    • pp.90-99
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    • 2003
  • Object clustering, which makes classification for a set of objects into a number of groups such that objects included in a group have similar characteristic and objects in different groups have dissimilar characteristic each other, has been exploited in diverse area such as information retrieval, data mining, group technology, etc. In this study, an object-clustering problem with similarity coefficients between objects is considered. At first, an evaluation function for the optimization problem is defined. Then, a genetic algorithm and local optimization technique based on heuristic method are proposed and used in order to obtain near optimal solutions. Solutions from the genetic algorithm are improved by local optimization techniques based on object relocation and cluster merging. Throughout extensive experiments, the validity and effectiveness of the proposed algorithms are tested.

Discovery Methods of Similar Web Service Operations by Learning Ontologies (온톨로지 학습에 의한 유사 웹 서비스 오퍼레이션 발견 방법)

  • Lee, Yong-Ju
    • The KIPS Transactions:PartD
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    • v.18D no.2
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    • pp.133-142
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    • 2011
  • To ensure the successful employment of semantic web services, it is essential that they rely on the use of high quality ontologies. However, building such ontologies is difficult and costly, thus hampering web service deployment. This study automatically builds ontologies from WSDL documents and their underlying semantics, and presents discovery methods of similar web service operations using these ontologies. The key ingredient is techniques that cluster parameters in the collection of web services into semantically meaningful concepts, and capture the hierarchical relationships between the words contained in the tag. We implement an operation retrieval system for web services. This system finds out a ranked set of similar operations using a novel similarity measurement method, and selects the most optimal operation which satisfies user's requirements. It can be directly used for the web services composition.

Fast Multi-Resolution Exhaustive Search Algorithm Based on Clustering for Efficient Image Retrieval (효율적인 영상 검색을 위한 클러스터링 기반 고속 다 해상도 전역 탐색 기법)

  • Song, Byeong-Cheol;Kim, Myeong-Jun;Ra, Jong-Beom
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.38 no.2
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    • pp.117-128
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    • 2001
  • In order to achieve optimal retrieval, i.e., to find the best match to a query according to a certain similarity measure, the exhaustive search should be performed literally for all the images in a database. However, the straightforward exhaustive search algorithm is computationally expensive in large image databases. To reduce its heavy computational cost, this paper presents a fast exhaustive multi-resolution search algorithm based on image database clustering. Firstly, the proposed algorithm partitions the whole image data set into a pre-defined number of clusters having similar feature contents. Next, for a given query, it checks the lower bound of distances in each cluster, eliminating disqualified clusters. Then, it only examines the candidates in the remaining clusters. To alleviate unnecessary feature matching operations in the search procedure, the distance inequality property is employed based on a multi-resolution data structure. The proposed algorithm realizes a fast exhaustive multi-resolution search for either the best match or multiple best matches to the query. Using luminance histograms as a feature, we prove that the proposed algorithm guarantees optimal retrieval with high searching speed.

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The Effects of Aging on Retrieval of Phonological Knowledge in Korean: The Tip-of-the-Tongue Phenomenon in Young and Older Adults (한국어 음운 정보 산출에서 노화의 영향: 청년과 노인의 설단현상)

  • Park, Jiyoon;Lee, Ko Eun;Lee, Hye-Won
    • Korean Journal of Cognitive Science
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    • v.24 no.2
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    • pp.111-132
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    • 2013
  • Previous research has shown that aging asymmetrically affects various functions in language. It is known that older adults show deficits in language production compared to young adults, while the performance in semantic processing is similar between older and young adults. The tip-of-the-tongue (TOT) phenomenon effectively reflects failure in retrieval of phonological knowledge. Older adults report TOTs more often than young adults and the cause of this phenomenon has been explained by two frameworks: the 'blocking hypothesis' and 'transmission deficit hypothesis'. This study examines the effect of aging on the retrival of phonological knowledge by inducing TOTs in the laboratory. Two variables were manipulated: age and word category. Participants were young and older adults, and stimuli was selected from 5 categories of words. After the participants read a definition about a target word, they reported three conditions: 'know', 'don't know', 'TOT'. The results were as follows: First, the older adults reported TOTs more often than the young adults. Second, TOTs occurred more in proper nouns such as names of persons and places. Third, in the category that TOTs occurred more often, there was a bigger age difference. Fourth, older adults reported fewer alternative words during TOT than young adults. Fifth, participants tended to report the partial information during TOT in characters. These results show the age-related difficulty in the retrieval of phonological knowledge in Korean. It is explained by the transmission deficit hypothesis and the characteristics of Korean orthography and phonology.

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Color Image Segmentation for Content-based Image Retrieval (내용기반 영상검색을 위한 칼라 영상 분할)

  • Lee, Sang-Hun;Hong, Choong-Seon;Kwak, Yoon-Sik;Lee, Dai-Young
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.9
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    • pp.2994-3001
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    • 2000
  • In this paper. a method for color image segmentation using region merging is proposed. A inhomogeneity which exists in image is reduced by smoothing with non-linear filtering. saturation enhancement and intensity averaging in previous step of image segmentation. and a similar regions are segmented by non-uniform quantization using zero-crossing information of color histogram. A edge strength of initial region is measured using high frequency energy of wavelet transform. A candidate region which is merged in next step is selected by doing this process. A similarity measure for region merging is processed using Euclidean distance of R. G. B color channels. A Proposed method can reduce an over-segmentation results by irregular light sources et. al, and we illustrated that the proposed method is reasonable by simulation.

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Review of Nursing Start-Up Literacy (간호창업에 대한 리터러시 고찰)

  • Lim, Ji Young;Kim, Juhang;Kim, Seulki
    • Journal of Home Health Care Nursing
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    • v.25 no.2
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    • pp.127-138
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    • 2018
  • Purpose: This study aimed to provide an overview of the present status of start-up literacy. Methods: The study selected literature from KoreaMed, RISS (Research Information Sharing Service), KISS (Korean studies Information Service System), KISTI (Korea Institute of Science and Technology Information), Ovid-MEDLINE (Medical Literature Analysis and Retrieval System Online), Embase, and Cochrane Library DB. Start-up curricula were collected from the homepage of nursing schools in Korea and the USA. Their contents were searched using Massive Open Online Course (MOOC) platforms; KOCW, K-MOOC, and Coursera. Results: Fifteen articles were selected through a systematic literature review. The main themes of nursing start-up were "driver," "barrier," "required competency," and "importance of education." The courses contained business planning, finance, marketing, leadership, and entrepreneurship. The main contents of MOOCs were similar. Conclusion: The results indicate the necessity to develop multi-scope nursing start-up education programs. Nursing start-up models integrated with appropriate business knowledge and skills in health care settings are needed. This study can be used as a guideline to design start-up education programs in nursing.

Similar Documents and Related Researcher Retrieval Method (유서문서 및 관련연구자 검색 방법)

  • Han, Hee-Jun
    • Proceedings of the Korean Information Science Society Conference
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    • 2010.06b
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    • pp.6-9
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    • 2010
  • 학술정보 이용자는 연구에 필요한 자료를 획득하기 위해 검색서비스를 이용한다. 대부분의 웹 이용자는 원하는 정보를 얻기 위해 수많은 검색 질의어를 생성하여 시스템에 요청하고 선별된 정보 리스트들을 탐색하고 정보획득의 최종 목적지로써 해당 정보의 상세화면으로 이동하게 된다. 마찬가지로 논문 및 특허 정보를 제공하는 학술정보서비스의 경우 이용자의 최종 목적지는 한 건의 상세 메타정보 혹은 원문이 되는데, 이 때 이용중인 정보와 유사한 다른 유형의 학술정보 및 관련 연구 분야의 연구자 제공 서비스는 이용자의 정보획득 요구를 쉽게 충족시키기 위한 필수요소이다. NDSL(국가과학기술종합정보서비스) 의 경우 동일 DB내에서의 유사문서 검색기능(논문검색에서는 유사논문 제공, 특허검색에서는 유사특허 제공)을 제공하지만 이는 이종 DB간 유사문서를 이용하고자 하는 사용자 요구사항을 만족시키지 못하는 수준이다. 본 논문에서는 논문, 특허, 연구보고서, 동향분석 자료를 포함한 학술정보 검색서비스에서 사용자 질의어와 검색엔진이 제공하는 검색 요소 및 부스팅(boosting) 기법을 이용한 이종 컨텐츠간 유사문서 리스트 및 관련 연구 분야의 연구자명 검색 서비스 기법에 대해 논한다. 이는 사용자가 원하는 학술정보를 서비스 최종 화면에서 효과적으로 제공함으로써 반복되는 검색 및 탐색의 노력을 줄일 수 있다.

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A Feature Re-weighting Approach for the Non-Metric Feature Space (가변적인 길이의 특성 정보를 지원하는 특성 가중치 조정 기법)

  • Lee Robert-Samuel;Kim Sang-Hee;Park Ho-Hyun;Lee Seok-Lyong;Chung Chin-Wan
    • Journal of KIISE:Databases
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    • v.33 no.4
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    • pp.372-383
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    • 2006
  • Among the approaches to image database management, content-based image retrieval (CBIR) is viewed as having the best support for effective searching and browsing of large digital image libraries. Typical CBIR systems allow a user to provide a query image, from which low-level features are extracted and used to find 'similar' images in a database. However, there exists the semantic gap between human visual perception and low-level representations. An effective methodology for overcoming this semantic gap involves relevance feedback to perform feature re-weighting. Current approaches to feature re-weighting require the number of components for a feature representation to be the same for every image in consideration. Following this assumption, they map each component to an axis in the n-dimensional space, which we call the metric space; likewise the feature representation is stored in a fixed-length vector. However, with the emergence of features that do not have a fixed number of components in their representation, existing feature re-weighting approaches are invalidated. In this paper we propose a feature re-weighting technique that supports features regardless of whether or not they can be mapped into a metric space. Our approach analyses the feature distances calculated between the query image and the images in the database. Two-sided confidence intervals are used with the distances to obtain the information for feature re-weighting. There is no restriction on how the distances are calculated for each feature. This provides freedom for how feature representations are structured, i.e. there is no requirement for features to be represented in fixed-length vectors or metric space. Our experimental results show the effectiveness of our approach and in a comparison with other work, we can see how it outperforms previous work.

New Methods for Correcting the Atmospheric Effects in Landsat Imagery over Turbid (Case-2) Waters

  • Ahn Yu-Hwan;Shanmugam P.
    • Korean Journal of Remote Sensing
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    • v.20 no.5
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    • pp.289-305
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    • 2004
  • Atmospheric correction of Landsat Visible and Near Infrared imagery (VIS/NIR) over aquatic environment is more demanding than over land because the signal from the water column is small and it carries immense information about biogeochemical variables in the ocean. This paper introduces two methods, a modified dark-pixel substraction technique (path--extraction) and our spectral shape matching method (SSMM), for the correction of the atmospheric effects in the Landsat VIS/NIR imagery in relation to the retrieval of meaningful information about the ocean color, especially from Case-2 waters (Morel and Prieur, 1977) around Korean peninsula. The results of these methods are compared with the classical atmospheric correction approaches based on the 6S radiative transfer model and standard SeaWiFS atmospheric algorithm. The atmospheric correction scheme using 6S radiative transfer code assumes a standard atmosphere with constant aerosol loading and a uniform, Lambertian surface, while the path-extraction assumes that the total radiance (L/sub TOA/) of a pixel of the black ocean (referred by Antoine and Morel, 1999) in a given image is considered as the path signal, which remains constant over, at least, the sub scene of Landsat VIS/NIR imagery. The assumption of SSMM is nearly similar, but it extracts the path signal from the L/sub TOA/ by matching-up the in-situ data of water-leaving radiance, for typical clear and turbid waters, and extrapolate it to be the spatially homogeneous contribution of the scattered signal after complex interaction of light with atmospheric aerosols and Raleigh particles, and direct reflection of light on the sea surface. The overall shape and magnitude of radiance or reflectance spectra of the atmospherically corrected Landsat VIS/NIR imagery by SSMM appears to have good agreement with the in-situ spectra collected for clear and turbid waters, while path-extraction over turbid waters though often reproduces in-situ spectra, but yields significant errors for clear waters due to the invalid assumption of zero water-leaving radiance for the black ocean pixels. Because of the standard atmosphere with constant aerosols and models adopted in 6S radiative transfer code, a large error is possible between the retrieved and in-situ spectra. The efficiency of spectral shape matching has also been explored, using SeaWiFS imagery for turbid waters and compared with that of the standard SeaWiFS atmospheric correction algorithm, which falls in highly turbid waters, due to the assumption that values of water-leaving radiance in the two NIR bands are negligible to enable retrieval of aerosol reflectance in the correction of ocean color imagery. Validation suggests that accurate the retrieval of water-leaving radiance is not feasible with the invalid assumption of the classical algorithms, but is feasible with SSMM.

Semantic Search System using Ontology-based Inference (온톨로지기반 추론을 이용한 시맨틱 검색 시스템)

  • Ha Sang-Bum;Park Yong-Tack
    • Journal of KIISE:Software and Applications
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    • v.32 no.3
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    • pp.202-214
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    • 2005
  • The semantic web is the web paradigm that represents not general link of documents but semantics and relation of document. In addition it enables software agents to understand semantics of documents. We propose a semantic search based on inference with ontologies, which has the following characteristics. First, our search engine enables retrieval using explicit ontologies to reason though a search keyword is different from that of documents. Second, although the concept of two ontologies does not match exactly, can be found out similar results from a rule based translator and ontological reasoning. Third, our approach enables search engine to increase accuracy and precision by using explicit ontologies to reason about meanings of documents rather than guessing meanings of documents just by keyword. Fourth, domain ontology enables users to use more detailed queries based on ontology-based automated query generator that has search area and accuracy similar to NLP. Fifth, it enables agents to do automated search not only documents with keyword but also user-preferable information and knowledge from ontologies. It can perform search more accurately than current retrieval systems which use query to databases or keyword matching. We demonstrate our system, which use ontologies and inference based on explicit ontologies, can perform better than keyword matching approach .